Unlike supervised learning where the model is trained using labeled data to predict outcomes, unsupervised learning works with unlabeled data. This type of machine learning is particularly useful when working with large datasets where manual labeling would be impractical. By finding patterns or features in the data, unsupervised learning can help us identify new trends, group similar data points, and even detect anomalies.
